Background: Congenital club foot is a complex deformity of foot .It is a collection of different abnormalities, with different etiologies. Consequently, Severity varies with   difficulties in evaluating treatment strategies with outcome results. The treatment of congenital club foot remains controversial. Usually, the orthopedist's goal is to obtain anatomically and functionally normal feet in all patients.                                Objective: To asses short term follow up result of conservatively treated club feet in relation to the age

the study aimed to identify the impact of the types of cooking utensils in transition metal elements to food and the effect of acid and storage in the concentration of these elements. used five types of cooking utensils including aluminum. tefal, astainls steel, glass. (pyrex), and ceramic prepared in it the food meal. the same meals were repeated add to them acid. the estimate of mineral elements in the meal prepared before storage and after storage in refrigerator temperature degree. the result shows the increase of aluminum concentration in the meals that prepared in aluminum pot reaching 2.913 pmm while reached less concentration in the meal prepared in astainls pot reaching 0.325 pmm. the highest concentration of iron reached 25.2 p

Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

Classifying butterfly species is crucial in biodiversity studies and environmental monitoring. However, manual classification is often a laborious process that requires specialized expertise and is prone to error, especially when species have similar visual characteristics. To address these drawbacks, this paper presents a hybrid approach that combines machine learning with deep learning for feature extraction. To enhance the visibility of important features, preprocessing techniques such as background removal and binarization are applied to butterfly images. Feature extraction was performed using the SqueezeNet convolutional neural network, pretrained on the ImageNet dataset. By discarding the final classification layer, the networ

The Journal of Studies and Researches of Sport Education (JSRSE)

The last four decades have witnessed a number of rapid and successive international changes in terms of future impacts and orientations. International economy has transformed into a competitive small village due to the information technology revolution and the liberation processes and the economic openness that the market witnesses, there became one market and the activists in this international market are not governments only but rather international organizations and huge multinational corporations where each spares no effort to take every opportunity and face challenges within the frame of  removing all impediments and release transactions under the auspices of  these global developments, the idea of creating Islamic

ولاء طارق حميد, Mustansiriyah Journal of Sports Science, 2021

The present research aims at recognizing the difficulties and problems which hamper teachers and educators alike when using the internet for educational purposes.It discusses the benefits of the internet as a source of information or publication and as a communicative tool.Arandom sample of (30) teachers working at schools in Baghdad / Second Risafa,was selected.Three of the sample members use the internet for student project plans via internet centers, whereas 16 of them use it for chatting, emailing and research purposes.The rest of the sample have limited knowledge of the internet. The researcher used the interviewing method to gather data from